Overview

Dataset statistics

Number of variables10
Number of observations2722028
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory207.7 MiB
Average record size in memory80.0 B

Variable types

Numeric10

Alerts

u is highly correlated with g and 8 other fieldsHigh correlation
g is highly correlated with u and 8 other fieldsHigh correlation
r is highly correlated with u and 8 other fieldsHigh correlation
i is highly correlated with u and 8 other fieldsHigh correlation
z is highly correlated with u and 8 other fieldsHigh correlation
uErr is highly correlated with u and 8 other fieldsHigh correlation
gErr is highly correlated with u and 8 other fieldsHigh correlation
rErr is highly correlated with u and 8 other fieldsHigh correlation
iErr is highly correlated with u and 8 other fieldsHigh correlation
zErr is highly correlated with u and 8 other fieldsHigh correlation
u is highly correlated with g and 8 other fieldsHigh correlation
g is highly correlated with u and 8 other fieldsHigh correlation
r is highly correlated with u and 8 other fieldsHigh correlation
i is highly correlated with u and 8 other fieldsHigh correlation
z is highly correlated with u and 8 other fieldsHigh correlation
uErr is highly correlated with u and 8 other fieldsHigh correlation
gErr is highly correlated with u and 8 other fieldsHigh correlation
rErr is highly correlated with u and 8 other fieldsHigh correlation
iErr is highly correlated with u and 8 other fieldsHigh correlation
zErr is highly correlated with u and 8 other fieldsHigh correlation
u is highly correlated with g and 4 other fieldsHigh correlation
g is highly correlated with u and 8 other fieldsHigh correlation
r is highly correlated with u and 7 other fieldsHigh correlation
i is highly correlated with g and 6 other fieldsHigh correlation
z is highly correlated with g and 6 other fieldsHigh correlation
uErr is highly correlated with u and 2 other fieldsHigh correlation
gErr is highly correlated with u and 8 other fieldsHigh correlation
rErr is highly correlated with u and 7 other fieldsHigh correlation
iErr is highly correlated with g and 6 other fieldsHigh correlation
zErr is highly correlated with g and 6 other fieldsHigh correlation
u is highly correlated with g and 8 other fieldsHigh correlation
g is highly correlated with u and 8 other fieldsHigh correlation
r is highly correlated with u and 8 other fieldsHigh correlation
i is highly correlated with u and 8 other fieldsHigh correlation
z is highly correlated with u and 8 other fieldsHigh correlation
uErr is highly correlated with u and 8 other fieldsHigh correlation
gErr is highly correlated with u and 8 other fieldsHigh correlation
rErr is highly correlated with u and 8 other fieldsHigh correlation
iErr is highly correlated with u and 8 other fieldsHigh correlation
zErr is highly correlated with u and 8 other fieldsHigh correlation

Reproduction

Analysis started2022-02-27 19:55:04.700281
Analysis finished2022-02-27 19:58:01.953629
Duration2 minutes and 57.25 seconds
Software versionpandas-profiling v3.1.1
Download configurationconfig.json

Variables

u
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct855059
Distinct (%)31.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.486448029
Minimum3.390798359
Maximum5.06395242
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size20.8 MiB
2022-02-27T16:58:02.004779image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum3.390798359
5-th percentile4.229034386
Q14.367990055
median4.510600884
Q34.595010216
95-th percentile4.703141131
Maximum5.06395242
Range1.673154062
Interquartile range (IQR)0.2270201612

Descriptive statistics

Standard deviation0.1484141654
Coefficient of variation (CV)0.03308054935
Kurtosis-0.5437861103
Mean4.486448029
Median Absolute Deviation (MAD)0.1026362228
Skewness-0.4255624828
Sum12212237.15
Variance0.0220267645
MonotonicityNot monotonic
2022-02-27T16:58:02.083065image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4.622617655362
 
< 0.1%
4.622618241313
 
< 0.1%
4.622617069254
 
< 0.1%
4.622618826222
 
< 0.1%
4.622619412101
 
< 0.1%
4.62261999873
 
< 0.1%
4.62261648470
 
< 0.1%
4.62262058332
 
< 0.1%
4.62261589824
 
< 0.1%
4.62262116921
 
< 0.1%
Other values (855049)2720556
99.9%
ValueCountFrequency (%)
3.3907983591
< 0.1%
3.5626783731
< 0.1%
3.7003032111
< 0.1%
3.7041061591
< 0.1%
3.7804833381
< 0.1%
3.7915296711
< 0.1%
3.8304683051
< 0.1%
3.8368845411
< 0.1%
3.8459355871
< 0.1%
3.8465073571
< 0.1%
ValueCountFrequency (%)
5.063952421
< 0.1%
5.0297457241
< 0.1%
4.9523335661
< 0.1%
4.9454878481
< 0.1%
4.9439171081
< 0.1%
4.9436203821
< 0.1%
4.943006581
< 0.1%
4.9423976771
< 0.1%
4.9386461851
< 0.1%
4.9354503181
< 0.1%

g
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct756885
Distinct (%)27.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.372520689
Minimum3.426885986
Maximum5.040429572
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size20.8 MiB
2022-02-27T16:58:02.192440image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum3.426885986
5-th percentile4.10858831
Q14.230409779
median4.427266912
Q34.485033897
95-th percentile4.553761674
Maximum5.040429572
Range1.613543586
Interquartile range (IQR)0.2546241182

Descriptive statistics

Standard deviation0.14998635
Coefficient of variation (CV)0.03430203323
Kurtosis-0.5723558053
Mean4.372520689
Median Absolute Deviation (MAD)0.08125174785
Skewness-0.6558970419
Sum11902123.75
Variance0.02249590518
MonotonicityNot monotonic
2022-02-27T16:58:02.281261image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4.650441754104
 
< 0.1%
4.6504411864
 
< 0.1%
4.65044232954
 
< 0.1%
4.65044290345
 
< 0.1%
4.47618075925
 
< 0.1%
4.46921981324
 
< 0.1%
4.46177213124
 
< 0.1%
4.4744821223
 
< 0.1%
4.46799869223
 
< 0.1%
4.46694877123
 
< 0.1%
Other values (756875)2721619
> 99.9%
ValueCountFrequency (%)
3.4268859861
< 0.1%
3.7489527821
< 0.1%
3.7628186521
< 0.1%
3.7825731651
< 0.1%
3.7920088481
< 0.1%
3.7949658051
< 0.1%
3.809549241
< 0.1%
3.8129807541
< 0.1%
3.8151224661
< 0.1%
3.8260348731
< 0.1%
ValueCountFrequency (%)
5.0404295721
< 0.1%
4.9850613621
< 0.1%
4.9819549171
< 0.1%
4.97833981
< 0.1%
4.9705854241
< 0.1%
4.9693512921
< 0.1%
4.9572729491
< 0.1%
4.9520106011
< 0.1%
4.9508407051
< 0.1%
4.9506979581
< 0.1%

r
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct685409
Distinct (%)25.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.278125623
Minimum3.799572269
Maximum4.52355882
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size20.8 MiB
2022-02-27T16:58:02.390636image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum3.799572269
5-th percentile4.039523017
Q14.148581113
median4.323320345
Q34.384934637
95-th percentile4.459876163
Maximum4.52355882
Range0.7239865512
Interquartile range (IQR)0.2363535237

Descriptive statistics

Standard deviation0.1393037058
Coefficient of variation (CV)0.03256185491
Kurtosis-0.6393827726
Mean4.278125623
Median Absolute Deviation (MAD)0.09464232507
Skewness-0.55434079
Sum11645177.73
Variance0.01940552245
MonotonicityNot monotonic
2022-02-27T16:58:02.484389image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4.36111563123
 
< 0.1%
4.36713199522
 
< 0.1%
4.34272895622
 
< 0.1%
4.35785106922
 
< 0.1%
4.36572472722
 
< 0.1%
4.37744377322
 
< 0.1%
4.35401130122
 
< 0.1%
4.35935459922
 
< 0.1%
4.35308611622
 
< 0.1%
4.36186448921
 
< 0.1%
Other values (685399)2721808
> 99.9%
ValueCountFrequency (%)
3.7995722691
< 0.1%
3.7995805571
< 0.1%
3.7995898821
< 0.1%
3.7996074951
< 0.1%
3.7996116391
< 0.1%
3.7996178551
< 0.1%
3.7996396121
< 0.1%
3.7996561881
< 0.1%
3.799678981
< 0.1%
3.7996903761
< 0.1%
ValueCountFrequency (%)
4.523558821
< 0.1%
4.5235575651
< 0.1%
4.5235556831
< 0.1%
4.5235437651
< 0.1%
4.5235400021
< 0.1%
4.5235362381
< 0.1%
4.5235268291
< 0.1%
4.5235249471
< 0.1%
4.5235230651
< 0.1%
4.5235061291
< 0.1%

i
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct675063
Distinct (%)24.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.224445154
Minimum3.064359504
Maximum4.984258486
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size20.8 MiB
2022-02-27T16:58:02.593759image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum3.064359504
5-th percentile4.002581916
Q14.112929445
median4.258870887
Q34.312862812
95-th percentile4.416755751
Maximum4.984258486
Range1.919898982
Interquartile range (IQR)0.1999333672

Descriptive statistics

Standard deviation0.1296779362
Coefficient of variation (CV)0.03069703391
Kurtosis-0.3174942897
Mean4.224445154
Median Absolute Deviation (MAD)0.08356154249
Skewness-0.4564246975
Sum11499057.99
Variance0.01681636713
MonotonicityNot monotonic
2022-02-27T16:58:02.687514image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4.60654882774
 
< 0.1%
4.60654941946
 
< 0.1%
4.30372815327
 
< 0.1%
4.29773801126
 
< 0.1%
4.29372581726
 
< 0.1%
4.28710285626
 
< 0.1%
4.28896312725
 
< 0.1%
4.29025703325
 
< 0.1%
4.29311441425
 
< 0.1%
4.29941831625
 
< 0.1%
Other values (675053)2721703
> 99.9%
ValueCountFrequency (%)
3.0643595041
< 0.1%
3.4994530381
< 0.1%
3.581657351
< 0.1%
3.6450710041
< 0.1%
3.7028459011
< 0.1%
3.7123129361
< 0.1%
3.7123305471
< 0.1%
3.7141300971
< 0.1%
3.7222321141
< 0.1%
3.7360214021
< 0.1%
ValueCountFrequency (%)
4.9842584861
< 0.1%
4.9649359611
< 0.1%
4.9611519221
< 0.1%
4.9576058811
< 0.1%
4.9470250761
< 0.1%
4.9463336431
< 0.1%
4.9406859331
< 0.1%
4.9379135421
< 0.1%
4.9343386311
< 0.1%
4.9306715871
< 0.1%

z
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct672835
Distinct (%)24.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.193566506
Minimum3.509876959
Maximum4.907709814
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size20.8 MiB
2022-02-27T16:58:02.785003image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum3.509876959
5-th percentile3.973647411
Q14.088367212
median4.224172664
Q34.278830781
95-th percentile4.397000633
Maximum4.907709814
Range1.397832855
Interquartile range (IQR)0.1904635687

Descriptive statistics

Standard deviation0.1290527713
Coefficient of variation (CV)0.03077398942
Kurtosis-0.0705562617
Mean4.193566506
Median Absolute Deviation (MAD)0.0771778234
Skewness-0.3506220362
Sum11415005.45
Variance0.01665461778
MonotonicityNot monotonic
2022-02-27T16:58:02.878756image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4.512663043563
 
< 0.1%
4.512663675328
 
< 0.1%
4.512662411167
 
< 0.1%
4.51266430788
 
< 0.1%
4.51266493941
 
< 0.1%
4.51266557131
 
< 0.1%
4.26147740929
 
< 0.1%
4.26432323928
 
< 0.1%
4.26704432928
 
< 0.1%
4.2813466227
 
< 0.1%
Other values (672825)2720698
> 99.9%
ValueCountFrequency (%)
3.5098769591
< 0.1%
3.6302353761
< 0.1%
3.6385233781
< 0.1%
3.6775127521
< 0.1%
3.6781147341
< 0.1%
3.6900616861
< 0.1%
3.6916279591
< 0.1%
3.6921392551
< 0.1%
3.6930174131
< 0.1%
3.6958090121
< 0.1%
ValueCountFrequency (%)
4.9077098141
< 0.1%
4.8769461311
< 0.1%
4.8710126771
< 0.1%
4.8666152561
< 0.1%
4.8599372561
< 0.1%
4.8589457861
< 0.1%
4.8563015171
< 0.1%
4.8527659391
< 0.1%
4.8513387831
< 0.1%
4.8489298481
< 0.1%

uErr
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2389824
Distinct (%)87.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-1.434831639
Minimum-8.667876248
Maximum5.539122821
Zeros0
Zeros (%)0.0%
Negative2000773
Negative (%)73.5%
Memory size20.8 MiB
2022-02-27T16:58:02.988143image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum-8.667876248
5-th percentile-4.869372974
Q1-3.018550919
median-0.8567770501
Q30.047874769
95-th percentile0.8304328913
Maximum5.539122821
Range14.20699907
Interquartile range (IQR)3.066425688

Descriptive statistics

Standard deviation1.877144742
Coefficient of variation (CV)-1.308268295
Kurtosis-0.6808896193
Mean-1.434831639
Median Absolute Deviation (MAD)1.133982021
Skewness-0.6678040976
Sum-3905651.897
Variance3.523672381
MonotonicityNot monotonic
2022-02-27T16:58:03.066254image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.097291211028
 
< 0.1%
0.20400921518
 
< 0.1%
0.18478681528
 
< 0.1%
0.057448885818
 
< 0.1%
0.23439953748
 
< 0.1%
0.026577707868
 
< 0.1%
0.27320553528
 
< 0.1%
0.10880677927
 
< 0.1%
0.16212236327
 
< 0.1%
0.42661579027
 
< 0.1%
Other values (2389814)2721951
> 99.9%
ValueCountFrequency (%)
-8.6678762481
< 0.1%
-8.3515823591
< 0.1%
-8.2016258471
< 0.1%
-8.0857296481
< 0.1%
-7.9851878711
< 0.1%
-7.9845925011
< 0.1%
-7.9625271131
< 0.1%
-7.9549969281
< 0.1%
-7.928850581
< 0.1%
-7.9245101071
< 0.1%
ValueCountFrequency (%)
5.5391228211
< 0.1%
5.2555743771
< 0.1%
5.2047072891
< 0.1%
4.8190274111
< 0.1%
4.7745809831
< 0.1%
4.7549425371
< 0.1%
4.6567217381
< 0.1%
4.4668411271
< 0.1%
4.4325485811
< 0.1%
4.395997781
< 0.1%

gErr
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2357695
Distinct (%)86.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-4.124869869
Minimum-9.072003501
Maximum5.362660295
Zeros0
Zeros (%)0.0%
Negative2707650
Negative (%)99.5%
Memory size20.8 MiB
2022-02-27T16:58:03.175629image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum-9.072003501
5-th percentile-7.491407586
Q1-6.275012705
median-3.509779691
Q3-2.568363563
95-th percentile-1.260035018
Maximum5.362660295
Range14.4346638
Interquartile range (IQR)3.706649142

Descriptive statistics

Standard deviation2.071773355
Coefficient of variation (CV)-0.502263931
Kurtosis-1.026591297
Mean-4.124869869
Median Absolute Deviation (MAD)1.329614386
Skewness-0.3212671191
Sum-11228011.28
Variance4.292244837
MonotonicityNot monotonic
2022-02-27T16:58:03.271275image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-3.1146724187
 
< 0.1%
-2.9139945757
 
< 0.1%
-2.963689397
 
< 0.1%
-2.9627937947
 
< 0.1%
-2.8404720787
 
< 0.1%
-3.2116985027
 
< 0.1%
-2.6671149737
 
< 0.1%
-2.7283391137
 
< 0.1%
-3.0303987957
 
< 0.1%
-3.0831571297
 
< 0.1%
Other values (2357685)2721958
> 99.9%
ValueCountFrequency (%)
-9.0720035011
< 0.1%
-9.0359069551
< 0.1%
-8.9798583951
< 0.1%
-8.9679817391
< 0.1%
-8.9538879531
< 0.1%
-8.9494577041
< 0.1%
-8.9436743151
< 0.1%
-8.9391308031
< 0.1%
-8.9322132771
< 0.1%
-8.9306045121
< 0.1%
ValueCountFrequency (%)
5.3626602951
< 0.1%
4.8009821891
< 0.1%
4.6555332991
< 0.1%
4.2223432141
< 0.1%
4.0712632681
< 0.1%
3.8411076451
< 0.1%
3.7622775831
< 0.1%
3.6218959711
< 0.1%
3.5726108011
< 0.1%
3.3669208521
< 0.1%

rErr
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2464413
Distinct (%)90.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-5.150489641
Minimum-9.057644664
Maximum-1.940751613
Zeros0
Zeros (%)0.0%
Negative2722028
Negative (%)100.0%
Memory size20.8 MiB
2022-02-27T16:58:03.365952image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum-9.057644664
5-th percentile-7.837512069
Q1-6.861997212
median-4.764985311
Q3-3.808233567
95-th percentile-2.593715951
Maximum-1.940751613
Range7.11689305
Interquartile range (IQR)3.053763645

Descriptive statistics

Standard deviation1.721509196
Coefficient of variation (CV)-0.3342418518
Kurtosis-1.162499474
Mean-5.150489641
Median Absolute Deviation (MAD)1.371718401
Skewness-0.1795792286
Sum-14019777.02
Variance2.96359391
MonotonicityNot monotonic
2022-02-27T16:58:03.459704image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-3.2772807836
 
< 0.1%
-3.2796549846
 
< 0.1%
-3.3088403596
 
< 0.1%
-3.2971091626
 
< 0.1%
-3.2786927946
 
< 0.1%
-3.2044604446
 
< 0.1%
-2.8891065526
 
< 0.1%
-4.4125632656
 
< 0.1%
-2.9679431796
 
< 0.1%
-2.6622583136
 
< 0.1%
Other values (2464403)2721968
> 99.9%
ValueCountFrequency (%)
-9.0576446641
< 0.1%
-9.0550454841
< 0.1%
-9.0520465821
< 0.1%
-9.0482669821
< 0.1%
-9.0463122391
< 0.1%
-9.0461391041
< 0.1%
-9.0436968311
< 0.1%
-9.043165491
< 0.1%
-9.0422144351
< 0.1%
-9.0419520541
< 0.1%
ValueCountFrequency (%)
-1.9407516131
< 0.1%
-1.9407565981
< 0.1%
-1.9407914922
< 0.1%
-1.9407942611
< 0.1%
-1.9408335871
< 0.1%
-1.9408579582
< 0.1%
-1.9408607271
< 0.1%
-1.9408834381
< 0.1%
-1.9408928541
< 0.1%
-1.9408934081
< 0.1%

iErr
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2416685
Distinct (%)88.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-5.481338672
Minimum-17.86008046
Maximum4.809064533
Zeros0
Zeros (%)0.0%
Negative2721423
Negative (%)> 99.9%
Memory size20.8 MiB
2022-02-27T16:58:03.569066image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum-17.86008046
5-th percentile-7.833942927
Q1-6.854766832
median-5.230101275
Q3-4.488836745
95-th percentile-2.977489689
Maximum4.809064533
Range22.669145
Interquartile range (IQR)2.365930086

Descriptive statistics

Standard deviation1.510037138
Coefficient of variation (CV)-0.2754869254
Kurtosis-0.6308609877
Mean-5.481338672
Median Absolute Deviation (MAD)1.081586949
Skewness0.03016363378
Sum-14920357.34
Variance2.280212158
MonotonicityNot monotonic
2022-02-27T16:58:03.662827image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-5.0886633747
 
< 0.1%
-6.5065835166
 
< 0.1%
-4.8746019676
 
< 0.1%
-6.6013155066
 
< 0.1%
-6.5740014456
 
< 0.1%
-5.7260608946
 
< 0.1%
-6.4644062886
 
< 0.1%
-5.1321113786
 
< 0.1%
-6.5785472136
 
< 0.1%
-5.2634885686
 
< 0.1%
Other values (2416675)2721967
> 99.9%
ValueCountFrequency (%)
-17.860080461
< 0.1%
-9.705037161
< 0.1%
-9.6418539651
< 0.1%
-9.4072736911
< 0.1%
-9.0905255731
< 0.1%
-9.0791147471
< 0.1%
-9.0705165681
< 0.1%
-9.0665506381
< 0.1%
-9.0658121041
< 0.1%
-9.0642620261
< 0.1%
ValueCountFrequency (%)
4.8090645331
< 0.1%
4.3722201211
< 0.1%
4.2518743351
< 0.1%
4.06181681
< 0.1%
4.0587771151
< 0.1%
3.8464000421
< 0.1%
3.8446728781
< 0.1%
3.8002641981
< 0.1%
3.7001922191
< 0.1%
3.5990987541
< 0.1%

zErr
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct2355495
Distinct (%)86.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-4.197201727
Minimum-11.04430682
Maximum5.428461681
Zeros0
Zeros (%)0.0%
Negative2714354
Negative (%)99.7%
Memory size20.8 MiB
2022-02-27T16:58:03.756577image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum-11.04430682
5-th percentile-6.741076826
Q1-5.486915348
median-3.939197105
Q3-3.184987004
95-th percentile-1.540930874
Maximum5.428461681
Range16.4727685
Interquartile range (IQR)2.301928344

Descriptive statistics

Standard deviation1.573221656
Coefficient of variation (CV)-0.3748263148
Kurtosis-0.3108389625
Mean-4.197201727
Median Absolute Deviation (MAD)1.025748282
Skewness0.0048595915
Sum-11424900.62
Variance2.475026378
MonotonicityNot monotonic
2022-02-27T16:58:03.838830image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-3.2256554459
 
< 0.1%
-3.2959496328
 
< 0.1%
-3.0629726598
 
< 0.1%
-3.2631267418
 
< 0.1%
-3.2676783488
 
< 0.1%
-3.0739070378
 
< 0.1%
-3.2241676438
 
< 0.1%
-3.225272228
 
< 0.1%
-3.2639441688
 
< 0.1%
-3.1666627
 
< 0.1%
Other values (2355485)2721948
> 99.9%
ValueCountFrequency (%)
-11.044306821
< 0.1%
-8.740563041
< 0.1%
-8.6757037861
< 0.1%
-8.6593476251
< 0.1%
-8.6389340411
< 0.1%
-8.6237729281
< 0.1%
-8.6229053111
< 0.1%
-8.621792681
< 0.1%
-8.6178255841
< 0.1%
-8.6020278361
< 0.1%
ValueCountFrequency (%)
5.4284616811
< 0.1%
5.1546273571
< 0.1%
4.837152571
< 0.1%
4.6596802841
< 0.1%
4.5351702231
< 0.1%
4.521128651
< 0.1%
4.5167861021
< 0.1%
4.4963524111
< 0.1%
4.4802121191
< 0.1%
4.4103160011
< 0.1%

Interactions

2022-02-27T16:57:45.697267image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:56:18.856158image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:56:28.533929image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:56:38.176421image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:56:47.866976image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:56:57.463917image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:57:07.109392image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:57:16.799584image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:57:26.473759image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:57:36.179523image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:57:46.658511image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:56:19.818425image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:56:29.494016image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:56:39.137448image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:56:48.811327image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:56:58.423757image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:57:08.082018image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:57:17.775126image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:57:27.441724image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:57:37.139964image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:57:47.634053image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:56:20.793156image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:56:30.450983image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:56:40.112967image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:56:49.787874image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:56:59.399168image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:57:09.058680image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:57:18.753145image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:57:28.427073image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:57:38.099353image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:57:48.596904image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:56:21.768573image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:56:31.412141image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:56:41.085950image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:56:50.732162image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:57:00.359032image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:57:10.034327image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:57:19.708989image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:57:29.401579image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:57:39.044749image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:57:49.553441image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:56:22.743815image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:56:32.387440image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:56:42.063008image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:56:51.689351image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:57:01.320098image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:57:11.009600image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:57:20.684485image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:57:30.373855image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:57:40.005047image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:57:50.526332image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:56:23.704805image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:56:33.347745image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:56:43.022274image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:56:52.666117image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:57:02.277420image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:57:11.969594image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:57:21.644909image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:57:31.350721image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:57:40.946143image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:57:51.487468image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:56:24.677490image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:56:34.308336image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:56:43.997756image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:56:53.625820image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:57:03.237328image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:57:12.940834image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:57:22.604483image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:57:32.326274image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:57:41.907192image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:57:52.447061image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:56:25.653529image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:56:35.280065image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:56:44.973939image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:56:54.586034image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:57:04.213734image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:57:13.903374image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:57:23.580835image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:57:33.285884image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:57:42.851392image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:57:53.407425image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:56:26.614770image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:56:36.241048image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:56:45.934310image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:56:55.531525image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:57:05.174533image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:57:14.880243image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:57:24.543923image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:57:34.261899image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:57:43.795679image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:57:54.352344image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:56:27.574293image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:56:37.201115image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:56:46.907093image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:56:56.498405image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:57:06.133716image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:57:15.838581image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:57:25.498160image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:57:35.222761image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:57:44.740041image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Correlations

2022-02-27T16:58:03.932568image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2022-02-27T16:58:04.041955image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2022-02-27T16:58:04.135705image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2022-02-27T16:58:04.245080image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Missing values

2022-02-27T16:57:54.528543image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
A simple visualization of nullity by column.
2022-02-27T16:57:55.500159image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

First rows

ugrizuErrgErrrErriErrzErr
04.6265284.4793344.4425954.4195934.421121-0.355339-3.336726-3.676320-3.601732-2.054881
14.5029654.4572574.4560834.4412044.450291-1.355431-3.687659-2.956998-2.538448-0.822430
24.7107164.4864034.4365364.4311924.452598-1.429789-3.167303-3.649887-3.269892-1.010986
34.6208634.4510504.4365834.4358234.471525-0.274045-4.040311-3.937535-3.320107-0.977932
44.6508594.5109594.4732324.4498424.466110-0.552079-2.900234-3.169031-3.157272-1.057521
54.5904884.5143414.4794654.4625694.485609-0.638633-2.954404-3.008676-2.879989-0.917506
64.5954644.7465024.3319124.2269994.3974981.355257-0.565750-4.021652-4.051302-0.188940
74.4464224.3757264.3373874.3318164.336153-2.851058-4.968574-5.292891-4.964696-3.101935
84.6611504.4577744.4096564.4033414.403371-0.632070-3.664285-4.244816-3.885261-2.226197
94.5877994.4698684.4391364.4341724.432422-0.861786-3.688879-3.702853-3.295795-1.719452

Last rows

ugrizuErrgErrrErriErrzErr
27220184.5272394.4829574.4284794.4003124.344791-0.732971-2.869584-3.060388-3.138966-2.158918
27220194.4405564.4176764.3878884.3726294.353696-2.992044-4.598663-4.621510-4.415295-3.147767
27220204.6337634.5322464.4289644.3440444.2763671.520788-0.775378-2.303812-3.334496-2.704285
27220214.3170524.2939554.2802614.2823804.273097-4.661460-6.264825-6.204331-5.687643-4.180041
27220224.3275114.2974024.2934434.2954644.328839-4.160500-6.102440-5.669864-5.200289-2.618014
27220234.4391524.4464344.4178844.4172044.426794-2.282216-3.449858-3.192773-2.606672-0.754991
27220244.4011884.4138624.4256844.4051324.390952-3.287110-4.154399-3.488137-3.296911-1.689056
27220254.4644624.4460294.4253654.4196374.381432-2.106479-4.136353-3.711797-3.317333-1.921612
27220264.4104774.3756874.3625484.3520964.359427-3.544141-5.336474-5.141721-4.889821-3.045029
27220274.4976824.4108424.3800364.3656974.365682-1.708628-4.375056-4.451421-4.167061-2.168564